BackgroundResearch on mortality and comorbidity associated with pelvic fractures in older patients is scarce. We aimed to determine the short- and long-term mortality rates of older patients with a pelvic ring fracture compared with both an age-matched cohort of patients with a femoral neck fracture and a general population, and to investigate 30- and 60-day readmission rates after pelvic fracture.MethodsThis was a retrospective cohort study done in an emergency department of a level II/III trauma center. All patients aged over 70 years diagnosed with a pelvic or acetabular fracture between January 2010 and December 2016 in our ED were identified. Two reference populations were used: patients operated due to femoral neck fracture in our institution between 2007 and 2008 and a general population aged 70 years or more.ResultsTwo hundred nineteen patients were identified. 30- and 90-day mortality was 7.3 and 11.4%, respectively. Compared to the general population, a pelvic fracture was associated with an 8.5-fold (95% CI: 5.2–13.9) and 11.0-fold (95% CI: 5.4–22.3) 90-day mortality risk in females and males, respectively. We could not observe a difference in the risk of 90-day mortality between femoral neck fracture patients and patients with a pelvic fracture. Within 30 days, 28 (12.8%) pelvic fracture patients were readmitted for in-patient care in our hospital.ConclusionsThe mortality of older patients with pelvic ring fractures resembles that after hip fracture. Although older patients with a pelvic ring fracture rarely require operative treatment, the severity of the injury should not be considered as a class apart from hip fracture.

Background Computed tomography angiography (CTA) imaging is needed in current guideline-based stroke diagnosis, and infarct core size is one factor in guiding treatment decisions. We studied the efficacy of a convolutional neural network (CNN) in final infarct volume prediction from CTA and compared the results to a CT perfusion (CTP)-based commercially available software (RAPID, iSchemaView). Methods We retrospectively selected 83 consecutive stroke cases treated with thrombolytic therapy or receiving supportive care that presented to Helsinki University Hospital between January 2018 and July 2019. We compared CNN-derived ischaemic lesion volumes to final infarct volumes that were manually segmented from follow-up CT and to CTP-RAPID ischaemic core volumes. Results An overall correlation of r = 0.83 was found between CNN outputs and final infarct volumes. The strongest correlation was found in a subgroup of patients that presented more than 9 h of symptom onset (r = 0.90). A good correlation was found between the CNN outputs and CTP-RAPID ischaemic core volumes (r = 0.89) and the CNN was able to classify patients for thrombolytic therapy or supportive care with a 1.00 sensitivity and 0.94 specificity. Conclusions A CTA-based CNN software can provide good infarct core volume estimates as observed in follow-up imaging studies. CNN-derived infarct volumes had a good correlation to CTP-RAPID ischaemic core volumes.

Background Computed tomography perfusion (CTP) is the mainstay to determine possible eligibility for endovascular thrombectomy (EVT), but there is still a need for alternative methods in patient triage. Purpose To study the ability of a computed tomography angiography (CTA)-based convolutional neural network (CNN) method in predicting final infarct volume in patients with large vessel occlusion successfully treated with endovascular therapy. Materials and Methods The accuracy of the CTA source image-based CNN in final infarct volume prediction was evaluated against follow-up CT or MR imaging in 89 patients with anterior circulation ischemic stroke successfully treated with EVT as defined by Thrombolysis in Cerebral Infarction category 2b or 3 using Pearson correlation coefficients and intraclass correlation coefficients. Convolutional neural network performance was also compared to a commercially available CTP-based software (RAPID, iSchemaView). Results A correlation with final infarct volumes was found for both CNN and CTP-RAPID in patients presenting 6–24 h from symptom onset or last known well, with r = 0.67 ( p < 0.001) and r = 0.82 ( p < 0.001), respectively. Correlations with final infarct volumes in the early time window (0–6 h) were r = 0.43 ( p = 0.002) for the CNN and r = 0.58 ( p < 0.001) for CTP-RAPID. Compared to CTP-RAPID predictions, CNN estimated eligibility for thrombectomy according to ischemic core size in the late time window with a sensitivity of 0.38 and specificity of 0.89. Conclusion A CTA-based CNN method had moderate correlation with final infarct volumes in the late time window in patients successfully treated with EVT.